Package: glmdisc
Type: Package
Title: Discretization and Grouping for Logistic Regression
Version: 0.6
Date: 2020-09-30
Authors@R: c(person("Adrien", "Ehrhardt", email = "adrien.ehrhardt@centraliens-lille.org",
                  role = c("aut", "cre")),
                  person("Vincent", "Vandewalle", email = "vincent.vandewalle@inria.fr",
                  role = c("aut")),
                  person("Christophe", "Biernacki", email = "christophe.biernacki@inria.fr",
                  role = c("ctb")),
                  person("Philippe", "Heinrich", email = "philippe.heinrich@univ-lille1.fr",
                  role = c("ctb")))
Maintainer: Adrien Ehrhardt <adrien.ehrhardt@centraliens-lille.org>
Description: A Stochastic-Expectation-Maximization (SEM) algorithm
        (Celeux et al. (1995) <https://hal.inria.fr/inria-00074164>)
        associated with a Gibbs sampler which purpose is to learn a
        constrained representation for logistic regression that is
        called quantization (Ehrhardt et al. (2019)
        <arXiv:1903.08920>). Continuous features are discretized and
        categorical features' values are grouped to produce a better
        logistic regression model. Pairwise interactions between
        quantized features are dynamically added to the model through a
        Metropolis-Hastings algorithm (Hastings, W. K. (1970)
        <doi:10.1093/biomet/57.1.97>).
License: GPL (>= 2)
Encoding: UTF-8
Imports: caret (>= 6.0-82), dplyr, magrittr, gam, nnet, RcppNumerical,
        methods, MASS, graphics, Rcpp (>= 0.12.13)
LinkingTo: Rcpp, RcppEigen, RcppNumerical
URL: https://adimajo.github.io
BugReports: https://github.com/adimajo/glmdisc/issues
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), covr
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'allClasses.R' 'cut.dataset.R'
        'discretize.link.R' 'generic_cutpoints.R'
        'generic_discretize.R' 'glmdisc.R' 'initialization.R'
        'method_cutpoints.R' 'method_discretize.R' 'method_plot.R'
        'method_predict.R' 'methods_disc.R' 'normalizedGini.R'
        'semDiscretization.R'
NeedsCompilation: yes
Packaged: 2026-11-14 10:31:28 UTC; root
Author: Adrien Ehrhardt [aut, cre], Vincent Vandewalle [aut],
        Christophe Biernacki [ctb], Philippe Heinrich [ctb]
Repository: https://cran.r-universe.dev
Date/Publication: 2020-09-30 20:10:02 UTC
RemoteUrl: https://github.com/cran/glmdisc
RemoteRef: HEAD
RemoteSha: d9ac9e4bd0f57a4c7a9189fc716f23a80b635d5a